This paper describes an object-oriented library for text classification called TMT (Text Mining Tools). We put forward the advantages of object-oriented design and describe the design requirements as well as the funct...
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ISBN:
(纸本)9789537138097
This paper describes an object-oriented library for text classification called TMT (Text Mining Tools). We put forward the advantages of object-oriented design and describe the design requirements as well as the functionalities of the library. We give an example of an integration of the TMT into an end-user application.
For the analysis of physiological signals, such as ECG's, continuous blood pressure recordings etc., access to the raw signal data as well as to processed data is mandatory. Up to now, there is no computer program...
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ISBN:
(纸本)0780384393
For the analysis of physiological signals, such as ECG's, continuous blood pressure recordings etc., access to the raw signal data as well as to processed data is mandatory. Up to now, there is no computer program which allows access to raw and processed data independently from the file formats used. Thus, programs have to be adapted to each new file format. The aim of the programming library 'libRASCH', is to provide an interface which allows the access to physiological signals in a consistent way. libRASCH is written in C and runs under Linux and Windows. The source code of libRASCH is published under the GNU LGPL. A plugin mechanism for extension of the library was implemented. Support for some widely used data formats (e.g. European Data Format) is already available. To support a new file-format, only the corresponding plugin has to be written. Moreover all programs using this library, can handle the new format without further adjustments. For other programming languages than C (e.g. Perl, Python), interfaces are available. On the libRASCH website (http://***), the source code of libRASCH and further information's are available.
The development of geostatistics has been mostly accomplished by application-oriented engineers in the past 20 years. The focus on concrete applications gave birth to many algorithms and computer programs designed to ...
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The development of geostatistics has been mostly accomplished by application-oriented engineers in the past 20 years. The focus on concrete applications gave birth to many algorithms and computer programs designed to address different issues, such as estimating or simulating a variable while possibly accounting for secondary information such as seismic data, or integrating geological and geometrical data. At the core of any geostatistical data integration methodology is a well-designed algorithm. Yet, despite their obvious differences, all these algorithms share many commonalities on which to build a geostatistics programming library, lest the resulting library is poorly reusable and difficult to expand. Building on this observation, we design a comprehensive, yet flexible and easily reusable library of geostatistics algorithms in C + +. The recent advent of the generic programming paradigm allows us elegantly to express the commonalities of the geostatistical algorithms into computer code. Generic programming, also referred to as "programming with concepts", provides a high level of abstraction without loss of efficiency. This last point is a major gain over object-oriented programming which often trades efficiency for abstraction. It is not enough for a numerical library to be reusable, it also has to be fast. Because generic programming is "programming with concepts", the essential step in the library design is the careful identification and thorough definition of these concepts shared by most geostatistical algorithms. Building on these definitions, a generic and expandable code can be developed. To show the advantages of such a generic library, we use G(S)TL to build two sequential simulation programs working on two different types of grids-a surface with faults and an unstructured grid-without requiring any change to the G(S)TL code. (C) 2002 Elsevier Science Ltd. All rights reserved.
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